Personal shopping services have traditionally been provided by an in-store sales associate, or by the hiring of a personal assistant. For instance, in a traditional situation, a customer enters a retail establishment and proceeds to ask a sales associate for assistance. The customer may have no preconceived notion of what they wish to buy and may utilize in-store assistance and/or personal advice to make a purchase. In still other situations, the customer may have an idea of the purchase they wish to make, and yet may still rely upon in-store personal assistance to make additional and/or other purchases based upon any number of factors including the associates recommendations, sales, advice, etc.
In a traditional on-line ecommerce setting, a customer visiting an on-line store front receives little or no assistance regarding their shopping experience. Moreover, receiving personal expertise from a sales associate that understands and knows a customer's likes/dislikes, trends, attitudes, etc. is difficult at best. Thus, in order to enhance the on-line experience, some on-line retailers have begun to provide additional enhancements to their shopping experience. For example, some websites provide customers with sales ranking, similar sales, on-line reviews, textual chats, etc. to assist an on-line customer in making purchase decisions.
These enhancements, however, are oftentimes generic in nature (e.g., what are the overall customer base trends) and do little to assist a buyer on a personal level. What is more, the customer may actually feel put off by the trends of other shoppers as the sophisticated consumer can typically recognize when a recommendation is impersonal and/or they wish to counter the prevailing style.
For example, US Patent Publication No. 2009/0132341 provides for a system and method of advertising utilizing user generated content. In particular, the method provides for a shift from a model of vendors hawking their own wares to a model of users promoting and selling products that the personally find valuable or useful, and rewarding those users selling goods according to the number of generated sales. In general, users with higher quality feedback will receive higher fees for executing product placements. The disclosed system, however, does not provide for a personalized shopping experience, but rather incentives an associate to peddle the most likely to sell product, thereby maximizing sales exposure regardless of the truly personal needs of the end consumer.
While the background systems and methods identified herein, generally work for their intended purpose, the subject invention provides improvements thereto, particularly by providing systems and methods provide for a personalized shopping experiences by tapping into a consumer's social network of individuals who know and understand the consumer on a personal level.